![]() Click Import parameter and fill the parameters. ![]() SET = 'Error Occured with the following Message ' + + 'Error Line Number '+ 50001, CATCHĬreate the SP in the database, go to Stored Procedure and select the SP. Step 2: Execute Update statement using the fixed (technical) columns Step 1: Extract schema and table name (based on the ADF pipeline naming convention) ![]() Parameter Parameter Date when the data was inserted into the Staging Name of a service / account that has inserted the data into the Staging table. In SSIS this was done by the Derived Column task. In ADF, without using Data Flows (Mapping), you can combine a Copy data activity with a Stored Procedure in order toįill those (technical) columns during execution of the pipeline. This query will load the following columns: We created a SP, that contains dynamic SQL to fill the columns "InsertedDate" and "InsertedBy" for every Staging table. In SQL Account, select the Linked service for Azure SQL Database that we created earlier. Click here for an example of naming convention in ADF.Īdd the Stored Procedure activity and give it a suitable name. This contributes to the extensibility and maintainability of your application. When working in a team, it is important to have a consistent way of development and have a proper naming convention in place. ![]() Of course you can implement this for every layer of your DWH. In this blog post we will focus on the Staging layer. The result will be a dynamic pipeline, that we can clone to create multiple pipelines using the same source and sink dataset. This will be a combination of parameters, variables and naming convention. One of the solutions is building dynamic pipelines. When using a "Copy Data Activity", you have to configure the mapping section when the source and sink fields are not equal.
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